37 citations · 151 across the 85 of their papers we have counts for
4 papers · 1 filter
Live LTL Progress Tracking: Towards Task-Based Exploration
Noel Brindise, Cedric Langbort, Melkior Ornik
Motivated by the challenge presented by non-Markovian objectives in reinforcement learning (RL), we present a novel framework to track and represent the progress of autonomous agen…
Capacity-Aware Planning and Scheduling in Budget-Constrained Multi-Agent MDPs: A Meta-RL Approach
Manav Vora, Ilan Shomorony, Melkior Ornik
We study capacity- and budget-constrained multi-agent MDPs (CB-MA-MDPs), a class that captures many maintenance and scheduling tasks in which each agent can irreversibly fail and a…
Solving Truly Massive Budgeted Monotonic POMDPs with Oracle-Guided Meta-Reinforcement Learning
Manav Vora, Jonas Liang, Michael N. Grussing +1
Monotonic Partially Observable Markov Decision Processes (POMDPs), where the system state progressively decreases until a restorative action is performed, can be used to model sequ…
Learning and Planning for Time-Varying MDPs Using Maximum Likelihood Estimation
Melkior Ornik, Ufuk Topcu
This paper proposes a formal approach to online learning and planning for agents operating in a priori unknown, time-varying environments. The proposed method computes the maximall…